Self-supervised learning and computer vision for robotic tasks
Thesis in external company
keywords ARTIFICIAL INTELLIGENCE, MACHINE LEARNING, MOBILE ROBOTICS
Reference persons FABRIZIO LAMBERTI
Research Groups DAUIN - GR-09 - GRAphics and INtelligent Systems - GRAINS
Thesis type THESIS WITH A COMPANY
Description Two thesis proposals in collaboration with Reply Spa are available in the context of self-supervised learning (SSL) and computer vision applied to mobile robots. In particular, the aim of the first thesis work is to develop new methods of SSL in computer vision in order to minimize the bottlenecks and problems of the classical methods of supervised and unsupervised learning. The goal is to adopt and improve an SSL model and then insert it into a real use case in industry or customer.
Masked Siamese Networks for Label-Efficient Learning
SSL method DINO
The objective of the second thesis work is to apply computer vision models to robotic agents such as Spot, by Boston Dynamics, or parcel delivery robots and other IOT devices. The difficulty of this work lies in being able to compress the power of the SSL models into lighter models capable of giving excellent results having scarce reserves both hardware and connectivity.
Robot Operating System
See also http://grains.polito.it/work.php
Deadline 31/07/2023 PROPONI LA TUA CANDIDATURA